Muhammad Taha Tariq | Robotics | Best Researcher Award

Published on by Best Achievements

Mr. Muhammad Taha Tariq | Robotics | Best Researcher Award

Mr. Muhammad Taha Tariq, Nanjing University of Aeronautics and Astronautics, China.

Muhammad Taha Tariq 🎓 is a dedicated researcher in Control Science and Engineering from Nanjing University of Aeronautics and Astronautics. His focus lies in 🤖 mobile robot path planning, using 🧠 Deep Reinforcement Learning and 🗺️ Large Language Models for dynamic navigation. With nationally funded projects and publications in top-tier venues, he brings innovation, precision, and AI-driven impact to the field. He is an active member of IEEE and ASME, continually pushing the boundaries of robotic intelligence.

🌟 Professional Profile

🎓 Early Academic Pursuits

Muhammad Taha Tariq began his academic journey with a strong inclination towards automation and artificial intelligence. He pursued a Master’s degree in Control Science and Engineering at Nanjing University of Aeronautics and Astronautics, where he built a robust foundation in machine learning, deep learning, and robotics. His early academic exposure shaped his research orientation toward practical innovation in intelligent systems, especially mobile robots and their navigation capabilities.

💼 Professional Endeavors

As a student researcher, Taha has embarked on ambitious projects combining theoretical excellence with practical implementations. He is affiliated with leading research programs and has actively contributed to funded projects, focusing on Deep Reinforcement Learning and Large Language Models. Despite being at an early stage of his career, his engagement with prestigious funding programs in China highlights his dedication and potential in academic research.

🔬 Contributions and Research Focus On Robotics 

Taha’s research specializes in mobile robot path planning, emphasizing dynamic environments and obstacle avoidance. His 2023–2024 project introduced a Deep Reinforcement Learning-based framework to calculate collision probabilities in real-time. In 2024–2025, he developed an innovative system that integrates LLMs for dynamic waypoint generation, achieving a 95.5% success rate and average task completion in 9.43 seconds. These contributions are both nationally funded and recognized through publications and technical demonstrations.

🌍 Impact and Influence

Though early in his career, Taha’s work reflects a deep commitment to open science. He provides preprints on arXiv, demonstration videos on YouTube, and open-source code on GitHub, fostering transparency and reproducibility in AI research. His methods are not only academically sound but also scalable for real-world robotic applications, influencing future trends in intelligent automation systems.

🏆 Awards and Honors

Taha has been nominated for the Best Researcher Award, a testament to his innovative work in automation and robotics. His selection is supported by successful national grants and active contributions to IEEE and ASME student communities.

📚 Academic Citations

As of now, Muhammad Taha Tariq does not report a citation index, but with publications accepted in journals like Expert Systems with Applications and conference presentations at the WRC Symposium, his research is gaining scholarly visibility and is poised to attract academic citations in the near future.

🚀 Legacy and Future Contributions

Muhammad Taha Tariq’s journey reflects a promising trajectory toward becoming a leading AI researcher. His legacy will likely include scalable frameworks for autonomous navigation and AI integration. Moving forward, he envisions enhancing robot-environment interaction using cutting-edge language models, contributing to safer and more efficient robotics applications in industries and smart cities.

📚Publications Top Notes

📄 1. Deep Reinforcement Learning-Based Path Planning with Dynamic Collision Probability for Mobile Robots

Geng Yang | Robot Sensing | Best Researcher Award

Published on by Best Achievements

Prof. Dr. Geng Yang | Robot Sensing | Best Researcher Award

Prof. Dr. Geng Yang, Zhejiang University, China.

Prof. Geng Yang is a distinguished researcher in robot sensing, human-robot interaction, and biomedical IoT. He is a Professor at the School of Mechanical Engineering, Zhejiang University, China, and previously held positions at Fudan University and the Royal Institute of Technology, Sweden. A recipient of China’s National Distinguished Young Talents Program, he serves as an Associate Editor for top IEEE journals. His pioneering work in human cyber-physical systems and flexible sensors has significantly advanced healthcare and industrial automation.

Professional Profile

🎓 Education

  • 2006—2013 🏅 Ph.D. in Electronic Systems, Royal Institute of Technology (KTH), Stockholm, Sweden
  • 2003—2006 🎓 M.Sc. in Instrument Science & Technology, Zhejiang University (ZJU), China
  • 1999—2003 📖 B.Sc. in Instrument Science & Technology, Zhejiang University (ZJU), China

🔬Research Contributions On Robot Sensing

Prof. Geng Yang has made significant contributions to robot sensing, human-robot interaction, and biomedical IoT, advancing safer and more efficient healthcare and industrial automation systems. His research on multimodal robot skin technology enhances tactile perception for human-cyber-physical systems. He has pioneered flexible circuits and biomedical micro-systems, integrating heterogeneous technologies for healthcare applications. His extensive publications, editorial roles, and leadership in IEEE and ACM conferences further solidify his impact in next-generation robotics, smart sensing, and assistive healthcare technologies.

💼 Work Experience

Prof. Geng Yang has an extensive academic and research career in mechanical engineering and biomedical systems. Since 2016, he has been a Professor at Zhejiang University, contributing to advancements in human-robot interaction and healthcare IoT. He previously served as an Associate Professor at Fudan University (2015–2016) and a Postdoctoral Researcher at the Royal Institute of Technology (KTH), Sweden (2013–2015). His expertise spans robot sensing, flexible circuits, and biomedical micro-systems, making significant contributions to academia and industry.

🏆 Editorial & Academic Contributions

  • Associate Editor:
    • IEEE Review in Biomedical Engineering (IEEE RBME)
    • Chinese Journal of Mechanical Engineering (CJME)
    • IEEE Journal of Biomedical and Health Informatics (IEEE JBHI)
    • Bio-Design and Manufacturing (Springer BDM)
  • Technical Committees: IEEE Industrial Electronics Society (IES)

🎤 Invited Talks & Tutorials (Recent)

  • Robot Tactile Perception for Safer Human-Robot Interaction – MDBS-BHE’ 2024, China 🇨🇳
  • Bionic Skin & Collaborative Robots in Healthcare 4.0 – Neural Engineering & Rehabilitation 2023, China
  • Multimodal Robot Skin for Safer Human-Robot Interaction – MDBS-CHE’ 2022, Hong Kong

Conclusion

Prof. Geng Yang’s exceptional contributions to robot sensing, human-robot interaction, and biomedical IoT establish him as a leader in research and innovation. His extensive publications, editorial roles, and global recognition underscore his impact. With a distinguished career and groundbreaking advancements, he is highly deserving of the Best Researcher Award for his remarkable achievements in science and technology.

📚Publication Top Notes

1️⃣ A health-IoT platform based on the integration of intelligent packaging, unobtrusive bio-sensor, and intelligent medicine box
📖 IEEE Transactions on Industrial Informatics (2014) – 865 citations 📊

2️⃣ Wearable Internet of Things: Concept, architectural components and promises for person-centered healthcare
📖 4th International Conference on Wireless Mobile Communication (2014) – 451 citations 🏥

3️⃣ An IoT-enabled stroke rehabilitation system based on smart wearable armband and machine learning
📖 IEEE Journal of Translational Engineering in Health and Medicine (2018) – 217 citations 🧠

4️⃣ IoT-based remote pain monitoring system: From device to cloud platform
📖 IEEE Journal of Biomedical and Health Informatics (2017) – 200 citations ☁️💉

5️⃣ Human Digital Twin in the context of Industry 5.0
📖 Robotics and Computer-Integrated Manufacturing (2024) – 197 citations 🤖

6️⃣ Homecare robotic systems for healthcare 4.0: Visions and enabling technologies
📖 IEEE Journal of Biomedical and Health Informatics (2020) – 197 citations 🏠🤖

7️⃣ Multifunctional flexible humidity sensor systems towards noncontact wearable electronics
📖 Nano-Micro Letters (2022) – 195 citations 🔬💧

8️⃣ Introduction to the special section: convergence of automation technology, biomedical engineering, and health informatics toward the healthcare 4.0
📖 IEEE Reviews in Biomedical Engineering (2018) – 185 citations 🏥🖥️

9️⃣ Stretchable graphene–hydrogel interfaces for wearable and implantable bioelectronics
📖 Nature Electronics (2024) – 153 citations 🧪🩺

🔟 Keep healthcare workers safe: application of teleoperated robot in isolation ward for COVID-19 prevention and control
📖 Chinese Journal of Mechanical Engineering (2020) – 153 citations 🦠🤖